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Normalizace pravopisu v arabských dialektech
dc.contributor.advisorZeman, Daniel
dc.creatorCayralat, Christian
dc.date.accessioned2021-09-29T09:55:35Z
dc.date.available2021-09-29T09:55:35Z
dc.date.issued2021
dc.identifier.urihttp://hdl.handle.net/20.500.11956/147949
dc.description.abstractOrthography Standardization in Arabic Dialects Abstract Christian Cayralat1 1 Charles University Spontaneous orthography in Arabic dialects poses one of the biggest ob- stacles in the way of Dialectal Arabic NLP applications. As the Arab world enjoys a wide array of these widely spoken and recently written, non-standard, low-resource varieties, this thesis presents a detailed account of this relatively overlooked phenomenon. It sets out to show that continuously creating addi- tional noise-free, manually standardized corpora of Dialectal Arabic does not free us from the shackles of non-standard (spontaneous) orthography. Because real-world data will most often come in a noisy format, it also investigates ways to ease the amount of noise in textual data. As a proof of concept, we restrict ourselves to one of the dialectal varieties, namely, Lebanese Arabic. It also strives to gain a better understanding of the nature of the noise and its distri- bution. All of this is done by leveraging various spelling correction and morpho- logical tagging neural architectures in a multi-task setting, and by annotating a Lebanese Arabic corpus for spontaneous orthography standardization, and morphological segmentation and tagging, among other features. Additionally, a detailed taxonomy of spelling inconsistencies for...en_US
dc.languageEnglishcs_CZ
dc.language.isoen_US
dc.publisherUniverzita Karlova, Matematicko-fyzikální fakultacs_CZ
dc.subjectspell checking|automatic corrections|Arabic|dialecten_US
dc.subjectkontrola pravopisu|automatické opravy|arabština|dialektcs_CZ
dc.titleOrthography Standardization in Arabic Dialectsen_US
dc.typediplomová prácecs_CZ
dcterms.created2021
dcterms.dateAccepted2021-09-08
dc.description.departmentInstitute of Formal and Applied Linguisticsen_US
dc.description.departmentÚstav formální a aplikované lingvistikycs_CZ
dc.description.facultyMatematicko-fyzikální fakultacs_CZ
dc.description.facultyFaculty of Mathematics and Physicsen_US
dc.identifier.repId235817
dc.title.translatedNormalizace pravopisu v arabských dialektechcs_CZ
dc.contributor.refereeStraňák, Pavel
thesis.degree.nameMgr.
thesis.degree.levelnavazující magisterskécs_CZ
thesis.degree.disciplineMatematická lingvistikacs_CZ
thesis.degree.disciplineComputational Linguisticsen_US
thesis.degree.programInformatikacs_CZ
thesis.degree.programComputer Scienceen_US
uk.thesis.typediplomová prácecs_CZ
uk.taxonomy.organization-csMatematicko-fyzikální fakulta::Ústav formální a aplikované lingvistikycs_CZ
uk.taxonomy.organization-enFaculty of Mathematics and Physics::Institute of Formal and Applied Linguisticsen_US
uk.faculty-name.csMatematicko-fyzikální fakultacs_CZ
uk.faculty-name.enFaculty of Mathematics and Physicsen_US
uk.faculty-abbr.csMFFcs_CZ
uk.degree-discipline.csMatematická lingvistikacs_CZ
uk.degree-discipline.enComputational Linguisticsen_US
uk.degree-program.csInformatikacs_CZ
uk.degree-program.enComputer Scienceen_US
thesis.grade.csVýborněcs_CZ
thesis.grade.enExcellenten_US
uk.abstract.enOrthography Standardization in Arabic Dialects Abstract Christian Cayralat1 1 Charles University Spontaneous orthography in Arabic dialects poses one of the biggest ob- stacles in the way of Dialectal Arabic NLP applications. As the Arab world enjoys a wide array of these widely spoken and recently written, non-standard, low-resource varieties, this thesis presents a detailed account of this relatively overlooked phenomenon. It sets out to show that continuously creating addi- tional noise-free, manually standardized corpora of Dialectal Arabic does not free us from the shackles of non-standard (spontaneous) orthography. Because real-world data will most often come in a noisy format, it also investigates ways to ease the amount of noise in textual data. As a proof of concept, we restrict ourselves to one of the dialectal varieties, namely, Lebanese Arabic. It also strives to gain a better understanding of the nature of the noise and its distri- bution. All of this is done by leveraging various spelling correction and morpho- logical tagging neural architectures in a multi-task setting, and by annotating a Lebanese Arabic corpus for spontaneous orthography standardization, and morphological segmentation and tagging, among other features. Additionally, a detailed taxonomy of spelling inconsistencies for...en_US
uk.file-availabilityV
uk.grantorUniverzita Karlova, Matematicko-fyzikální fakulta, Ústav formální a aplikované lingvistikycs_CZ
thesis.grade.code1
uk.publication-placePrahacs_CZ
uk.thesis.defenceStatusO


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